Discover Awesome MCP Servers

Message Control Protocol (MCP) Server

A REST API server implementation for message handling with Oracle Database integration via ODBC, offering endpoints for creating and retrieving messages with comprehensive error handling.

Tavily Web Search MCP Server

Enables web search capabilities through the Tavily API. Allows users to search the web for information using natural language queries via the MCP protocol.

Appium MCP Server

Enables AI-powered mobile app testing and automation through Appium, using Azure OpenAI to intelligently navigate mobile applications and generate test cases.

Bitrefill MCP Server

Espejo de

zan-mcp-server

Servidor de Protocolo de Contexto de Modelo para el Servicio de Nodo ZAN.

MCPServerTransportDemo

A demonstration project for building and testing Model Context Protocol (MCP) servers using the MCP inspector and client tools. It provides a practical implementation for exploring MCP transport mechanisms and server-client interactions.

Zulip MCP Server

A Model Context Protocol server that enables AI assistants to interact with Zulip workspaces by exposing REST API capabilities as tools for message operations, channel management, and user interactions.

Google AdWords MCP Server by CData

Google AdWords MCP Server by CData

MCP Hello World Example

Un proyecto plantilla para crear proyectos de servidor y cliente MCP.

MCP-Demo: Model Context Protocol Integration with OpenAI

Ejemplo inicial de cliente-servidor del SDK MCP de C#

ADM1 MCP Server

Enables natural language control of anaerobic digestion modeling using the internationally recognized ADM1 standard. Supports wastewater treatment simulation for process design and optimization with AI-powered feedstock analysis, multi-reactor configurations, and professional report generation.

CC Explorer MCP Server

Enables AI assistants to query the Canton Network blockchain explorer through the CC Explorer Pro API. It provides tools for accessing ledger updates, governance votes, validator information, and network consensus data.

MCP Git Server

A Model Context Protocol server that enables LLMs to interact with Git repositories, providing tools to read, search, and manipulate Git repositories through commands like status, diff, commit, and branch operations.

Cursor Agent Poisoning

A proof-of-concept attack that exploits Model Context Protocol (MCP) tool registration to achieve persistent agent poisoning in AI assistants like Cursor, embedding malicious instructions that persist across chat contexts without requiring tool execution.

MCP to LangChain/LangGraph Adapter

Okay, I understand. You want a Python adapter that takes tools designed for an MCP (presumably Minecraft Protocol) server and makes them usable as tools within the Langchain framework. Here's a conceptual outline and a code snippet to get you started. This is a basic example and will need to be adapted to your specific MCP server tools and Langchain setup. **Conceptual Outline** 1. **Understand MCP Server Tools:** You need to know how to interact with your MCP server tools. This likely involves sending commands over a network connection (e.g., TCP socket) and parsing the responses. You'll need to define the specific commands each tool accepts and the format of the data it returns. 2. **Langchain Tool Interface:** Langchain tools have a specific interface. They need a `name`, a `description`, and a `_run` method (or `arun` for asynchronous execution) that takes a string as input and returns a string as output. 3. **Adapter Class:** Create a Python class that inherits from `langchain.tools.BaseTool`. This class will: * Initialize with the necessary connection details for your MCP server. * Implement the `_run` method to: * Connect to the MCP server. * Format the input string into a command suitable for the MCP server tool. * Send the command to the server. * Receive the response from the server. * Parse the response. * Return the parsed response as a string. * Define the `name` and `description` attributes for the tool. **Code Snippet (Basic Example)** ```python from langchain.tools import BaseTool import socket import json # Assuming your MCP server uses JSON for communication class MCPServerTool(BaseTool): """Tool for interacting with an MCP server.""" name: str = "mcp_server_tool" # Replace with a more descriptive name description: str = ( "Useful for interacting with a Minecraft server. " "Input should be a JSON string containing the 'command' and any necessary 'arguments'." ) host: str = "localhost" # Replace with your MCP server's host port: int = 25565 # Replace with your MCP server's port def _run(self, query: str) -> str: """Use the tool.""" try: query_json = json.loads(query) command = query_json.get("command") arguments = query_json.get("arguments", {}) # Default to empty dict if no arguments if not command: return "Error: 'command' key missing in the input JSON." # Format the command for the MCP server (adjust as needed) mcp_command = self._format_mcp_command(command, arguments) # Connect to the MCP server with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: s.connect((self.host, self.port)) s.sendall(mcp_command.encode()) # Encode to bytes # Receive the response (adjust buffer size as needed) response = s.recv(1024).decode() # Decode from bytes # Parse the response (assuming JSON) try: response_json = json.loads(response) return json.dumps(response_json) # Return as JSON string except json.JSONDecodeError: return f"MCP Server Response: {response}" # Return raw response if not JSON except json.JSONDecodeError: return "Error: Invalid JSON input." except Exception as e: return f"Error: {e}" async def _arun(self, query: str) -> str: """Use the tool asynchronously.""" raise NotImplementedError("This tool does not support asynchronous execution.") def _format_mcp_command(self, command: str, arguments: dict) -> str: """Formats the command for the MCP server. Adjust this based on your server's protocol.""" # Example: Assuming the server expects commands like "command arg1=value1 arg2=value2" command_string = command for key, value in arguments.items(): command_string += f" {key}={value}" return command_string ``` **How to Use** 1. **Replace Placeholders:** Fill in the `host`, `port`, `name`, and `description` attributes with the correct values for your MCP server and tool. 2. **Implement `_format_mcp_command`:** This is crucial. This method *must* format the input `command` and `arguments` into the exact format that your MCP server expects. This will vary depending on your server's protocol. 3. **Adjust Socket Communication:** The `socket` code might need adjustments. Consider: * **Buffering:** The `recv(1024)` call receives up to 1024 bytes. If your server sends larger responses, you'll need to receive in a loop until you have the complete response. * **Encoding:** Make sure you're using the correct encoding (e.g., UTF-8) for both sending and receiving data. * **Error Handling:** Add more robust error handling (e.g., timeouts, connection errors). 4. **Parse Responses:** The code assumes the server returns JSON. If it returns a different format, you'll need to change the parsing logic accordingly. 5. **Add to Langchain:** Instantiate the `MCPServerTool` and add it to your Langchain agent's tools list. ```python # Example of adding the tool to a Langchain agent from langchain.agents import initialize_agent from langchain.llms import OpenAI # Or your preferred LLM # Replace with your OpenAI API key openai_api_key = "YOUR_OPENAI_API_KEY" llm = OpenAI(temperature=0, openai_api_key=openai_api_key) mcp_tool = MCPServerTool() tools = [mcp_tool] agent = initialize_agent(tools, llm, agent="zero-shot-react-description", verbose=True) # Example usage prompt = """ What is the current time on the Minecraft server? The input to this tool should be a json string with the command and arguments. """ # The agent will call the tool with an input like: # '{"command": "get_time", "arguments": {}}' # Assuming your _format_mcp_command formats it correctly. agent.run(prompt) ``` **Important Considerations** * **Security:** Be extremely careful about security. Never expose your MCP server directly to the internet without proper security measures. Sanitize all input to prevent command injection vulnerabilities. Consider using authentication and authorization. * **Error Handling:** Implement robust error handling to catch exceptions and provide informative error messages. * **Asynchronous Execution:** If you need asynchronous execution, you'll need to use `asyncio` and asynchronous socket operations. The `_arun` method in the example raises `NotImplementedError`. * **MCP Server Protocol:** The most important part is understanding and correctly implementing the communication protocol with your MCP server. Consult your server's documentation or source code for details. * **Langchain Agent Type:** The `zero-shot-react-description` agent is a good starting point, but you might need to experiment with different agent types to find one that works best for your use case. This comprehensive response should give you a solid foundation for building your MCP server tool adapter for Langchain. Remember to adapt the code to your specific needs and prioritize security. Good luck!

Crash MCP Server

Enables AI assistants to analyze Linux system crash dumps by automatically discovering dump files, matching kernels, and executing interactive crash analysis commands through the MCP protocol.

SAP SuccessFactors MCP Server by CData

SAP SuccessFactors MCP Server by CData

MCPBrowser

Fetches content from authenticated web pages by driving your signed-in Chrome/Edge browser via DevTools Protocol, automatically handling login redirects and reusing sessions across domains.

SEO Audit MCP Server

Provides comprehensive technical SEO auditing tools including page analysis, site crawling, Lighthouse performance testing, and sitemap analysis, with specialized features for job board websites like JobPosting schema validation.

Twelve Data MCP Server

Provides integration with Twelve Data API to access financial market data including historical time series, real-time quotes, and instrument metadata for stocks, forex pairs, and cryptocurrencies.

vet-mcp

vet-mcp

@mcp/openverse

An MCP server that enables searching and fetching openly-licensed images from Openverse with features like filtering by license type, getting image details, and finding essay-specific illustrations.

Local Services MCP Server

A Multi-Agent Conversation Protocol Server that provides access to Google's Local Services API, enabling interaction with local service businesses information through natural language commands.

OCI Core Services FastMCP Server

A dedicated server for Oracle Cloud Infrastructure (OCI) Core Services that enables management of compute instances and network operations with LLM-friendly structured responses.

mcp-server-email MCP server

I am a language model, and I don't have an email address. I am accessed through interfaces provided by Google.

Singapore News MCP Server

Provides real-time news feeds from major Singapore news sources including The Straits Times, Business Times, and Channel News Asia. Delivers live news updates through Server-Sent Events for up-to-date information access.

Tongyi Wanxiang MCP Server

A TypeScript-based Model Context Protocol server that enables large language models to directly invoke Alibaba Cloud's Tongyi Wanxiang text-to-image generation API.

MCPify

A dynamic proxy that converts OpenAPI Specification (OAS) endpoints into Message Communication Protocol (MCP) tools, allowing AI agents to use existing REST APIs as if they were native MCP tools without manual implementation.

Hong Kong Transportation MCP Server

An MCP server providing access to Hong Kong transportation data, including passenger traffic statistics at control points and real-time bus arrival information for KMB and Long Win Bus services.